'''
Author: SlytherinGe
LastEditTime: 2021-04-10 20:14:42
'''
_base_ = [
    '../_base_/datasets/vedai_detection.py',
    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
    type='RetinaNet',
    pretrained='/home/gejunyao/.cache/torch/hub/checkpoints/backup/resnet50-19c8e357.pth',
    backbone=dict(
        type='ResNet',
        depth=50,
        num_stages=4,
        out_indices=(0, 1, 2, 3),
        frozen_stages=1,
        norm_cfg=dict(type='BN', requires_grad=True),
        norm_eval=True,
        style='pytorch'),
    neck=dict(
        type='FPN',
        in_channels=[256, 512, 1024, 2048],
        out_channels=256,
        start_level=1,
        add_extra_convs='on_input',
        num_outs=5),
    bbox_head=dict(
        type='RetinaHead',
        num_classes=9,
        in_channels=256,
        stacked_convs=4,
        feat_channels=256,
        anchor_generator=dict(
            type='AnchorGenerator',
            octave_base_scale=4,
            scales_per_octave=3,
            ratios=[0.5, 1.0, 2.0],
            strides=[8, 16, 32, 64, 128]),
        bbox_coder=dict(
            type='DeltaXYWHBBoxCoder',
            target_means=[.0, .0, .0, .0],
            target_stds=[1.0, 1.0, 1.0, 1.0]),
        loss_cls=dict(
            type='FocalLoss',
            use_sigmoid=True,
            gamma=2,
            alpha=0.25,
            loss_weight=1.0),
        loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
    # training and testing settings
    train_cfg=dict(
        assigner=dict(
            type='MaxIoUAssigner',
            pos_iou_thr=0.5,
            neg_iou_thr=0.4,
            min_pos_iou=0,
            ignore_iof_thr=-1),
        allowed_border=-1,
        pos_weight=-1,
        debug=False),
    test_cfg=dict(
        nms_pre=1000,
        min_bbox_size=0,
        score_thr=0.05,
        nms=dict(type='nms', iou_threshold=1),
        max_per_img=1000))



data = dict(
    samples_per_gpu=18,
    workers_per_gpu=16)
# optimizer
optimizer = dict(type='SGD', lr=0.0004, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
runner = dict(type='EpochBasedRunner', max_epochs=48)
# learning policy
lr_config = dict(
    policy='step',
    warmup='linear',
    warmup_iters=50,
    warmup_ratio=0.001,
    step=[36, 40, 46])
log_config = dict(
    interval=10,
    hooks=[
        dict(type='TextLoggerHook'),
        # dict(type='TensorboardLoggerHook')
    ])
# _base_ = [
#     '../_base_/models/retinanet_r50_fpn.py', '../_base_/datasets/vedai_detection.py',
#     '../_base_/default_runtime.py'
# ]
# model = dict(bbox_head=dict(num_classes=11))
# # optimizer
# optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
# optimizer_config = dict(grad_clip=None)
# # learning policy
# # actual epoch = 3 * 3 = 9
# lr_config = dict(policy='step', step=[3])
# # runtime settings
# runner = dict(
#     type='EpochBasedRunner', max_epochs=4)  # actual epoch = 4 * 3 = 12
